Artificial Intelligence-Enabled Electrocardiography for Monitoring Serum Potassium Dynamics in Patients With Severe Hypokalemia.

Abstract

Rationale & objective: Severe hypokalemia requires prompt management and close surveillance. Although artificial intelligence-enabled electrocardiography (AI-ECG) rapidly detects severe hypokalemia, its application for monitoring serum potassium (K⁺) dynamics during treatment remains unexplored. This study assessed AI-ECG performance in monitoring K⁺ changes during supplementation.

Study design: Multicenter retrospective cohort study.

Setting & participants: 191 adults with severe hypokalemia (Lab-K⁺ ≤2.5 mmol/L; matched ECG-K⁺ <3.5 mmol/L) and ≥1 follow-up paired measurement within 24 hours of K⁺ supplementation at three teaching hospitals between September 2019 and August 2024.

Tests compared: Laboratory-measured K⁺ (Lab-K⁺) and K⁺ estimated by ECG (ECG-K⁺) overall and stratified by the etiology of hypokalemia (acute K⁺ shift vs. chronic K⁺ deficit).

Outcomes: Primary: agreement between paired ECG-K⁺ and Lab-K⁺. Secondary: diagnostic accuracy and K⁺ trajectories.

Analytical approach: Linear mixed-effects models with patient-level random intercepts; repeated-measures correlation (rmcorr) and Bland-Altman plots; patient-level clustered bootstrapped ROC analysis for diagnostic accuracy.

Results: Of 191 patients, 156 (81.7%) had chronic K⁺ deficits (most commonly gastrointestinal disorders [n=47] or diuretic use [n=35]), and 35 (18.3%) had acute K⁺ shifts (most commonly thyrotoxic periodic paralysis [n=25]). The chronic K⁺ deficits group had more comorbidities and use of medications affecting K⁺. ECG-K⁺ correlated strongly with Lab-K⁺ (rmcorr 0.847; 95% CI, 0.81-0.88; p<0.001). The relationship was modified by hypokalemia etiology (interaction p<0.0001) with a lower correlation in patients with chronic K⁺ deficits. The diagnostic accuracy of ECG-K⁺ with Lab-K⁺ ≤3.5 mmol/L was reflected by an AUC of 0.920; 95% CI, 0.863-0.961. It was higher in patients with acute K⁺ shift. ECG-K⁺ preceded Lab-K⁺ results by a mean of 52.5 minutes. Patients with acute K⁺ shift corrected approximately threefold faster than those with chronic K⁺ deficit (0.121 vs. 0.039 mmol/L/h). Rebound hyperkalemia was detected by ECG-K⁺ in two patients before laboratory confirmation.

Limitations: Retrospective design; treatment-protocol heterogeneity; limited inpatient medication granularity and potential selection bias.

Conclusions: AI-ECG enables real-time, within-patient monitoring of serum K⁺ dynamics during treatment for severe hypokalemia, with superior performance in the setting of acute hypokalemia due to K⁺ shift. As a non-invasive adjunct, AI-ECG may shorten time to detect changes in K⁺ and reduce the need for laboratory K⁺ measurements than exclusive reliance on Lab-K⁺ measurements. Confirmatory studies are warranted.